code: def feature_importance(self, df, classification=False):
      if classification == True:
          df2 = self.data.feature_importance_classification(df)
          names = list(df2["VariableName"])
          new_names = []
          for n in names:
              new_names.append(n.strip("_impact"))
          df2["VariableName"] = new_names
          return df2
      else:
          df2 = self.data.feature_importance(df)
          names = list(df2["VariableName"])
          new_names = []
          for n in names:
              new_names.append(n.strip("_impact"))
          df2["VariableName"] = new_names
          return df2
  
file_path: explainx/lib/plotly_graphs.py
imports: from imports import *
  from feature_impact import *
  from feature_importance import *
  from shap_pdp import *
  from summary_plot import *
  from data_for_shap_graphs import *
label_desc: Use image node_id 2 for calling the plotly_graphs obj's underlying member method code with example usage: obj.feature_importance(df, classification) and returns: df2, df2